Research on a High-Precision State-of-Charge Estimation Method Based on Forgetting Factor Recursive Least Squares and Adaptive Extended Kalman Filter Applied to LiFePO4 Battery

Research on a High-Precision State-of-Charge Estimation Method Based on Forgetting Factor Recursive Least Squares and Adaptive Extended Kalman Filter Applied to LiFePO4 Battery

The state-of-charge (SOC) estimation accuracy is closely associated with the estimation method and the battery parameter identification performance. The battery parameter identification method based on forgetting factor recursive least squares (FFRLS) has the advantages of high parameter identificat...

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Bibliographic Details
Main Authors: Yihui Xia, Zhihao Ye, Liming Huang, Lucheng Sun, Yunxiang Jiang
Format: Article
Language:English
Published: MDPI AG 2023-08-01
Series:Electronics
Subjects:
LiFePO4 battery
high precision
FFRLS
AEKF
SOC estimation
Online Access:https://www.mdpi.com/2079-9292/12/17/3670

Internet

https://www.mdpi.com/2079-9292/12/17/3670

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